Uric acid-to-high-density lipoprotein cholesterol ratio and osteoporosis: Evidence from the national health and nutrition examination survey

Abstract

Background: The uric acid-to-high-density lipoprotein cholesterol ratio (UHR) has emerged as a novel indicator of inflammatory and metabolic status. This study aims to examine the association between UHR and bone mineral density (BMD), as well as the risk of osteoporosis, in individuals aged ≥50 years. Methods: This cross-sectional study used data from the National Health and Nutrition Examination Survey, focusing on participants aged ≥50 years. Femoral neck BMD (FN-BMD) was measured using dual-energy X-ray absorptiometry. Linear regression models were employed to examine the association between UHR and FN-BMD. Additionally, generalised additive models were used to assess the nonlinear relationship between UHR and FN-BMD. Logistic regression models were employed to evaluate the association between UHR and the risk of osteoporosis. Results: Finally, the study included 2963 adults with a mean age of 64.16 ± 8.92 years. Linear regression analyses revealed a positive association between UHR and FN-BMD, regardless of covariate adjustments. Logistic regression analyses indicated that elevated UHR was associated with a reduced risk of osteoporosis with or without covariate adjustments. Subgroup analyses revealed that the positive association between UHR and BMD was significant in individuals aged ≥65 years but not in those aged 50 to 64 years. Interaction analyses by age showed significant differences after adjusting for all covariates. Conclusions: Clinicians should be vigilant regarding the potential risk of osteoporosis in individuals with a low UHR. UHR might serve as a risk indicator for osteoporosis.

Keywords

bone mineral density high-density lipoprotein cholesterol national health and nutrition examination survey osteoporosis uric acid

Background

Osteoporosis is a systemic musculoskeletal disorder characterised by reduced bone mineral density (BMD) and the deterioration of bone tissue microstructure.¹ It is notable for its high prevalence, affecting approximately one-third of females and one-fifth of males aged ≥50 years globally.^2–4 An epidemiological study in China revealed an osteoporosis prevalence of 5.0% among males and 20.6% among females aged ≥40 years.⁵ As the population continues to age, the prevalence of osteoporosis is expected to rise.^6,7 Moreover, osteoporosis imposes significant financial and societal burdens, with annual costs estimated at $17.9 billion in the United States (US) and £4 billion in the United Kingdom.⁸ The disorder is also associated with high rates of disability and mortality, particularly due to serious complications such as osteoporotic fractures, including hip fractures, which significantly affect the health and quality of life of elderly individuals.^9–11 Therefore, early prevention of osteoporosis is a crucial focus of ongoing research.

Investigating both risk and protective factors for diseases is crucial for developing effective early prevention strategies. Osteoporosis, from a pathological viewpoint, encompasses a complex interplay of bone metabolism, hormonal regulation, and immune modulation.^1,12 The aetiology of osteoporosis is associated with a range of factors.^1,12,13 Evidence indicated that key risk factors include age, sex, menopausal status, race, physical activity levels, and nutritional intake.^13,14 Furthermore, numerous studies have suggested that using these risk factors to identify and predict osteoporosis risk can be an effective strategy for early detection and prevention.^15,16 Therefore, there is a growing emphasis on investigating the factors associated with osteoporosis in current research.

The uric acid (UA)-to-high-density lipoprotein cholesterol (HDL-C) ratio (UHR) is a novel marker indicative of metabolic and inflammatory conditions. Previous research has linked UHR to an increased risk of various illnesses and demonstrated its potential as a predictor for several clinical outcomes.^17–20 Xie et al. found that a high UHR was independently associated with the risk and severity of non-alcoholic fatty liver disease in the American population, with correlations varying by sex.²⁰ Zhu et al. posited that elevated UHR could serve as a cost-effective and reliable predictor for the onset of non-alcoholic fatty liver disease in non-obese Chinese individuals with normal blood lipid levels.²¹ Furthermore, Yang et al. identified an association between elevated UHR and an increased likelihood of adverse cardiovascular events in individuals with chronic total occlusion of the coronary arteries.²² Yang et al. also demonstrated that the combined presence of high UA and low HDL-C had a synergistic effect on risk stratification for acute myocardial infarction.²³ These findings suggest that UHR might serve as a valuable and independent prognostic marker, complementing traditional risk factors. However, the relationship between UHR and osteoporosis risk remains to be definitively established. Further research is needed to explore this association and potentially identify early predictive markers for osteoporosis.

This study aims to examine the correlation between UHR and BMD, as well as the risk of osteoporosis, using data from the National Health and Nutrition Examination Survey (NHANES). Our hypothesis posited that elevated UHR would be positively correlated with higher BMD and a reduced risk of osteoporosis.

Methods

Study design and population

This cross-sectional study used data from the NHANES 2017–March 2020 cycle. NHANES is a biennial survey conducted by the National Centre for Health Statistics (NCHS) to evaluate the health and nutritional status of the US population. All participants provided written informed consent, and the study was approved by the Institutional Review Board of the NCHS. Participants were included if they met the following criteria: (i) aged ≥50 years, (ii) had complete BMD data, and (iii) had complete UHR data. Individuals with missing data on covariates were excluded from the analysis. Additional details are available on the NHANES website.²⁴

BMD measurement and osteoporosis

BMD was measured using dual-energy X-ray absorptiometry, with femoral neck BMD (FN-BMD) selected as the outcome variable due to its established association with hip fracture risk.²⁵ Osteoporosis was defined based on BMD results and the World Health Organisation criteria, where a T-score of ≤ −2.5 for FN-BMD is indicative of osteoporosis. Specific values for FN-BMD were derived from previous studies (BMD: ≤0.588 g/cm² for males and ≤0.560 g/cm² for females).^26–28 Detailed information on the BMD measurement methodology is available on the NHANES website.²⁹

UHR assessment

In this study, UHR was considered the exposure variable. According to a previous study,¹⁸ UHR is calculated using the formula: UHR (%) = UA (mg/dL)/HDL-C (mg/dL). Detailed procedures for measuring UA and HDL-C are available on the NHANES website.³⁰

Covariates

To account for potential confounding variables that could influence both the outcome and exposure variables, this study included multiple covariates in the analyses. The covariates considered were as follows: age; sex/menopausal status (post-menopausal women, pre-menopausal women, or men); race (non-Hispanic White, non-Hispanic Black, Mexican American, or other races); education level (below high school, high school or equivalent, or above high school); body mass index (BMI) categories (normal: BMI <25 kg/m²; overweight: 25≤ BMI <30 kg/m²; or obese: BMI ≥30 kg/m²); smoking status (never, former, or current); drinking status (never, former, or current); physical activity; vitamin D intake; calcium intake; milk product consumption (never, rarely, sometimes, often, or varied); history of diabetes (yes or no); history of arthritis (yes or no); history of cancer (yes or no); history of fractures (yes or no); history of glucocorticoid use (yes or no); alanine aminotransferase (U/L); aspartate aminotransferase (U/L); alkaline phosphatase (IU/L); blood urea nitrogen (BUN) (mmol/L); serum creatinine (mg/dL); serum calcium (mg/dL); serum total cholesterol (mg/dL); serum triglycerides (TGs) (mg/dL); serum HDL-C; and serum UA (mg/dL). Detailed information on the assessment of these covariates is available on the NHANES website.²⁴

Statistical analysis

Baseline characteristics are reported as the mean ± standard deviation for continuous variables and as n (%) for categorical variables. Differences in baseline characteristics among groups stratified by UHR were assessed using one-way analysis of variance for continuous variables and the chi-square test for categorical variables. Linear regression models were employed to investigate the association between UHR and FN-BMD, while logistic regression models were employed to examine the association between UHR and osteoporosis risk. The nonlinear relationship between UHR and FN-BMD was explored using generalised additive models. Furthermore, subgroup analyses and interaction tests were performed to evaluate the relationship between UHR and BMD, as well as the risk of osteoporosis, across different populations categorised by age, sex/menopausal status, race/ethnicity, and BMI. UHR values were also converted from a continuous variable to a categorical variable (quartile 1 to quartile 4) (Q1-Q4) to examine their association with FN-BMD and osteoporosis risk. Data analysis was conducted using R software version 4.2.1 (https://cran.r-project.org/) and EmpowerStats version 2.0 (https://www.empowerstats.com). A significance level of p < .05 was used to determine statistical significance.

Results

Selection of the study population

This study initially included 15,560 participants from the NHANES 2017–March 2020 cycle. Participants aged <50 years and those with missing data on BMD, UHR, or relevant covariates were excluded. Ultimately, 2963 participants aged ≥50 years were retained for the final analysis. A detailed flowchart illustrating the inclusion and exclusion criteria is presented in Figure 1.

Figure 1.

Flowchart of the study population selection process. BMD: bone mineral density; NHANES: national health and nutrition examination survey; UHR, uric acid to high-density lipoprotein cholesterol ratio.

Baseline characteristics

A total of 2963 adults were included in this study, with a mean age of 64.16 ± 8.92 years. The average HDL-C level was 54.59 ± 16.28 mg/dL, and the mean UA level was 5.53 ± 1.46 mg/dL. Among the participants, 27.81% were post-menopausal women, 18.93% were pre-menopausal women, and 53.26% were males. When UHR was categorised into quartiles, significant differences were observed among the UHR groups in terms of FN-BMD and the prevalence of osteoporosis (p < .001). Specifically, participants with a higher UHR exhibited a higher BMD and a lower prevalence of osteoporosis compared to those with lower UHR. Detailed baseline characteristics are presented in Table 1.

Table 1.

Baseline characteristics of study population.

Characteristics	Total	UHR (Q1)	UHR (Q2)	UHR (Q3)	UHR (Q4)	p-value
Characteristics	N = 2963	N = 739	N = 742	N = 740	N = 742	p-value
Age (years)	64.16 ± 8.92	63.91 ± 9.08	63.82 ± 8.84	64.42 ± 9.03	64.46 ± 8.71	.372
Sex/menopausal status, n (%)						<.001
Post-menopausal women	824 (27.81%)	337 (45.60%)	242 (32.61%)	168 (22.70%)	77 (10.38%)
Pre-menopausal women	561 (18.93%)	227 (30.72%)	153 (20.62%)	112 (15.14%)	69 (9.30%)
Men	1578 (53.26%)	175 (23.68%)	347 (46.77%)	460 (62.16%)	596 (80.32%)
Race, n (%)						.062
Non-Hispanic White	1209 (40.80%)	320 (43.30%)	288 (38.81%)	313 (42.30%)	288 (38.81%)
Non-Hispanic Black	731 (24.67%)	168 (22.73%)	194 (26.15%)	197 (26.62%)	172 (23.18%)
Mexican American	283 (9.55%)	59 (7.98%)	74 (9.97%)	74 (10.00%)	76 (10.24%)
Other races	740 (24.97%)	192 (25.98%)	186 (25.07%)	156 (21.08%)	206 (27.76%)
Education level, n (%)						<.001
Under high school	535 (18.06%)	101 (13.67%)	130 (17.52%)	142 (19.19%)	162 (21.83%)
High school or equivalent	738 (24.91%)	170 (23.00%)	197 (26.55%)	184 (24.86%)	187 (25.20%)
Above high school	1690 (57.04%)	468 (63.33%)	415 (55.93%)	414 (55.95%)	393 (52.96%)
BMI status, n (%)						<.001
Normal BMI	690 (23.29%)	302 (40.87%)	171 (23.05%)	139 (18.78%)	78 (10.51%)
Overweight	1119 (37.77%)	283 (38.29%)	295 (39.76%)	273 (36.89%)	268 (36.12%)
Obesity	1154 (38.95%)	154 (20.84%)	276 (37.20%)	328 (44.32%)	396 (53.37%)
Smoking status, n (%)						<.001
Never	1571 (53.02%)	445 (60.22%)	405 (54.58%)	370 (50.00%)	351 (47.30%)
Former	931 (31.42%)	190 (25.71%)	209 (28.17%)	237 (32.03%)	295 (39.76%)
Currently	461 (15.56%)	104 (14.07%)	128 (17.25%)	133 (17.97%)	96 (12.94%)
Drinking status, n (%)						.101
Never	269 (9.08%)	74 (10.01%)	70 (9.43%)	70 (9.46%)	55 (7.41%)
Former	788 (26.59%)	183 (24.76%)	187 (25.20%)	190 (25.68%)	228 (30.73%)
Currently	1906 (64.33%)	482 (65.22%)	485 (65.36%)	480 (64.86%)	459 (61.86%)
Physical activity (h/day)	10.81 ± 17.88	10.01 ± 17.17	11.89 ± 19.64	10.93 ± 17.47	10.39 ± 17.11	.202
Vitamin D intake (mcg/day)	0.39 ± 1.41	0.49 ± 1.70	0.37 ± 1.05	0.41 ± 1.75	0.29 ± 0.92	.048
Calcium intake (mcg/day)	13.14 ± 8.65	15.31 ± 9.75	13.80 ± 8.92	12.11 ± 7.70	11.34 ± 7.53	<.001
Milk product consumption, n (%)						.425
Never	672 (22.68%)	191 (25.85%)	156 (21.02%)	160 (21.62%)	165 (22.24%)
Rarely	595 (20.08%)	149 (20.16%)	139 (18.73%)	145 (19.59%)	162 (21.83%)
Sometimes	797 (26.90%)	186 (25.17%)	209 (28.17%)	211 (28.51%)	191 (25.74%)
Often	895 (30.21%)	211 (28.55%)	237 (31.94%)	223 (30.14%)	224 (30.19%)
Varied	4 (0.13%)	2 (0.27%)	1 (0.13%)	1 (0.14%)	0 (0.00%)
History of hypertension, n (%)						<.001
Yes	1587 (53.56%)	335 (45.33%)	363 (48.92%)	417 (56.35%)	472 (63.61%)
No	1376 (46.44%)	404 (54.67%)	379 (51.08%)	323 (43.65%)	270 (36.39%)
History of diabetes, n (%)						<.001
Yes	660 (22.27%)	98 (13.26%)	142 (19.14%)	189 (25.54%)	231 (31.13%)
No	2303 (77.73%)	641 (86.74%)	600 (80.86%)	551 (74.46%)	511 (68.87%)
History of arthritis, n (%)						.380
Yes	1319 (44.52%)	344 (46.55%)	338 (45.55%)	315 (42.57%)	322 (43.40%)
No	1644 (55.48%)	395 (53.45%)	404 (54.45%)	425 (57.43%)	420 (56.60%)
History of cancer, n (%)						.504
Yes	487 (16.44%)	123 (16.64%)	109 (14.69%)	126 (17.03%)	129 (17.39%)
No	2476 (83.56%)	616 (83.36%)	633 (85.31%)	614 (82.97%)	613 (82.61%)
History of fractures, n (%)						.781
Yes	427 (14.41%)	100 (13.53%)	113 (15.23%)	110 (14.86%)	104 (14.02%)
No	2536 (85.59%)	639 (86.47%)	629 (84.77%)	630 (85.14%)	638 (85.98%)
History of glucocorticoid use, n (%)						.679
Yes	211 (7.12%)	48 (6.50%)	56 (7.55%)	58 (7.84%)	49 (6.60%)
No	2752 (92.88%)	691 (93.50%)	686 (92.45%)	682 (92.16%)	693 (93.40%)
Alanine aminotransferase (U/L)	21.70 ± 14.82	19.61 ± 13.04	20.83 ± 14.17	22.01 ± 17.44	24.36 ± 13.85	<.001
Aspartate aminotransferase (U/L)	22.18 ± 11.70	22.27 ± 11.20	21.61 ± 9.91	21.80 ± 13.67	23.05 ± 11.69	.082
Alkaline phosphatase (IU/L)	81.80 ± 25.64	81.36 ± 25.93	82.25 ± 26.85	82.02 ± 26.45	81.59 ± 23.22	.909
Blood urea nitrogen (mmol/L)	16.52 ± 6.15	15.06 ± 5.10	15.55 ± 4.81	16.78 ± 5.71	18.70 ± 7.85	<.001
Serum creatinine (mg/dL)	0.95 ± 0.42	0.82 ± 0.41	0.90 ± 0.43	0.96 ± 0.38	1.11 ± 0.40	<.001
Serum calcium (mg/dL)	9.31 ± 0.39	9.33 ± 0.38	9.29 ± 0.39	9.31 ± 0.38	9.29 ± 0.41	.213
Total cholesterol (mg/dL)	190.64 ± 43.77	203.09 ± 39.92	194.77 ± 42.66	183.96 ± 43.19	180.75 ± 45.59	<.001
Triglyceride (mg/dL)	143.88 ± 98.51	101.37 ± 45.25	127.92 ± 62.72	146.48 ± 74.88	199.57 ± 148.52	<.001
HDL-C (mg/dL)	54.59 ± 16.28	72.76 ± 16.09	57.21 ± 9.94	48.46 ± 8.20	40.00 ± 7.03	<.001
UA (mg/dL)	5.53 ± 1.46	4.15 ± 0.87	5.14 ± 0.91	5.82 ± 0.97	7.03 ± 1.25	<.001
Femur neck BMD (g/cm²)	0.77 ± 0.15	0.72 ± 0.14	0.77 ± 0.15	0.79 ± 0.15	0.82 ± 0.14	<.001
Bone status, n (%)						<.001
Non-osteoporosis	2780 (93.82%)	657 (88.90%)	695 (93.67%)	704 (95.14%)	724 (97.57%)
Osteoporosis	183 (6.18%)	82 (11.10%)	47 (6.33%)	36 (4.86%)	18 (2.43%)

Normal BMI <25 kg/m², overweight 25 ≤ BMI <30 kg/m², obesity BMI ≥30 kg/m².

BMD: bone mineral density; BMI: body mass index, HDL-C: high-density lipoprotein cholesterol; UA: uric acid; UHR: uric acid to high-density lipoprotein cholesterol ratio.

Covariate screening

Covariates with a p-value of <.1 in the univariate linear regression analysis (with FN-BMD as the outcome) were selected for further analysis. Finally, all covariates except for education level, milk product consumption, history of arthritis, BUN, and TGs were included in the subsequent analysis. For detailed participant information, please refer to Supplemental Table S1. Multicollinearity between UHR and the included covariates was evaluated using variance inflation factor (VIF) values, with a VIF of >5 indicating multicollinearity. The results indicated no multicollinearity between UHR and the included covariates. Additional details are provided in Supplemental Table S2.

Association between UHR and BMD

Linear regression analyses revealed a positive association between UHR and FN-BMD in individuals aged ≥50 years with or without adjustment for covariates. Subgroup analyses further demonstrated that this positive association was observed in individuals aged ≥65 years, Whites, those with normal BMI, and obese participants after adjusting for all covariates. Additionally, interaction analysis highlighted significant differences based on age, though no significant interactions were observed for other stratification factors after adjustment for all covariates. Detailed results are presented in Table 2. Lastly, nonlinear fitting indicated that FN-BMD increased with increasing UHR values, as illustrated in Figure 2.

Table 2.

Association between UHR and FN-BMD.

Population	Model 1			Model 2			Model 3
Population	β (95% CI)	p-value	P interaction	β (95% CI)	p-value	P interaction	β (95% CI)	p-value	P interaction
Overall	0.0065 (0.0055, 0.0075)	<.0001	—	0.0014 (0.0004, 0.0024)	.0044	—	0.0014 (0.0004, 0.0024)	.0051	—
Age^a			0.5020			0.0168			0.0331
50–64 years	0.0064 (0.0051, 0.0078)	<.0001		0.0004 (−0.0010, 0.0018)	.5589		0.0010 (−0.0004, 0.0024)	.1649
65 years and older	0.0071 (0.0057, 0.0086)	<.0001		0.0023 (0.0009, 0.0038)	.0014		0.0022 (0.0007, 0.0036)	.0040
Sex/menopausal status^b			0.1002			0.8037			0.6346
Post-menopausal women	0.0060 (0.0037, 0.0082)	<.0001		0.0019 (−0.0002, 0.0040)	.0802		0.0018 (−0.0005, 0.0042)	.1185
Pre-menopausal women	0.0027 (0.0006, 0.0048)	.0139		0.0018 (−0.0001, 0.0037)	.0587		0.0018 (−0.0001, 0.0037)	.0605
Men	0.0034 (0.0020, 0.0048)	.0001		0.0013 (−0.0001, 0.0027)	.0659		0.0013 (−0.0001, 0.0027)	.0698
Race/ethnicity^c			0.4820			0.3536			0.3386
Non-Hispanic White	0.0062 (0.0048, 0.0076)	<.0001		0.0016 (0.0002, 0.0031)	.0245		0.0016 (0.0001, 0.0030)	.0366
Non-Hispanic Black	0.0063 (0.0041, 0.0085)	<.0001		0.0019 (−0.0004, 0.0041)	.1028		0.0020 (−0.0003, 0.0044)	.0829
Mexican American	0.0044 (0.0013, 0.0076)	.0062		0.0009 (−0.0025, 0.0042)	.6145		0.0013 (−0.0024, 0.0049)	.4980
Other races	0.0075 (0.0057, 0.0094)	<.0001		0.0005 (−0.0014, 0.0025)	.5987		0.0002 (−0.0018, 0.0023)	.8243
BMI^d			0.2530			0.3621			0.3058
Normal BMI	0.0061 (0.0040, 0.0083)	<.0001		0.0019 (−0.0002, 0.0041)	.0734		0.0024 (0.0002, 0.0046)	.0360
Overweight	0.0043 (0.0026, 0.0061)	.0001		0.0002 (−0.0016, 0.0020)	.8313		0.0004 (−0.0015, 0.0022)	.7067
Obesity	0.0038 (0.0023, 0.0053)	.0659		0.0019 (0.0005, 0.0033)	.0087		0.0018 (0.0004, 0.0033)	.0154

Model 1: no covariates were adjusted; Model 2: age, sex/menopausal status, race/ethnicity, and BMI were adjusted; Model 3: all covariates were adjusted.

BMD: bone mineral density; BMI: body mass index; FN: femoral neck; UHR: uric acid to high-density lipoprotein cholesterol ratio.

^aAge was not adjusted.

^bSex/menopausal status was not adjusted.

^cRace/ethnicity was not adjusted.

^dBMI was not adjusted.

Figure 2.

Non-linear relationship between UHR and FN-BMD. (a) Model 1; (b) Model 2; (c) Model 3. Model 1: no covariates were adjusted; Model 2: age, sex/menopausal status, race/ethnicity, and BMI were adjusted; Model 3: all covariates were adjusted. Red line represents the fitting curve; blue line represents the 95% CI. BMD: bone mineral density; BMI: body mass index; CI: confidence interval; FN: femoral neck; UHR: uric acid to high-density lipoprotein cholesterol ratio.

Association between UHR and osteoporosis risk

The logistic regression analysis revealed that UHR was negatively associated with osteoporosis risk in individuals aged ≥50 years, regardless of whether covariates were adjusted for. Subgroup analysis further showed that this negative association was consistent in males, Whites, Blacks, those with normal BMI, and obese participants. Additionally, interaction analysis indicated that no significant interactions were observed after adjusting for covariates. The detailed data are provided in Table 3.

Table 3.

Association between UHR and the risk of osteoporosis.

Population	Model 1			Model 2			Model 3
Population	OR (95% CI)	p-value	P interaction	OR (95% CI)	p-value	P interaction	OR (95% CI)	p-value	P interaction
Overall	0.8670 (0.8323, 0.9032)	<.0001	—	0.9347 (0.8931, 0.9783)	.0037	—	0.9148 (0.8716, 0.9602)	.0003	—
Age^a			0.3849			0.8686			0.8600
50–64 years	0.8349 (0.7716, 0.9034)	.0001		0.9503 (0.8731, 1.0343)	.2379		0.9072 (0.8254, 0.9972)	.0437
65 years and older	0.8697 (0.8281, 0.9133)	<.0001		0.9337 (0.8852, 0.9849)	.0119		0.9233 (0.8728, 0.9767)	.0054
Sex/menopausal status^b			0.6869			0.7163			0.9477
Post-menopausal women	0.8902 (0.8248, 0.9607)	.0028		0.9594 (0.8840, 1.0412)	.3211		0.9082 (0.8203, 1.0057)	.0641
Pre-menopausal women	0.9225 (0.8483, 1.0032)	.0595		0.9443 (0.8684, 1.0268)	.1801		0.9137 (0.8295, 1.0064)	.0673
Men	0.8795 (0.8210, 0.9421)	.0003		0.9028 (0.8384, 0.9722)	.0068		0.9080 (0.8417, 0.9794)	.0125
Race/ethnicity^c			0.2837			0.2353			0.2237
Non-Hispanic White	0.8926 (0.8509, 0.9364)	.0001		0.9412 (0.8915, 0.9936)	.0285		0.9196 (0.8676, 0.9747)	.0048
Non-Hispanic Black	0.7877 (0.6654, 0.9324)	.0055		0.8397 (0.7012, 1.0055)	.0574		0.7977 (0.6397, 0.9949)	.0449
Mexican American	0.8634 (0.6998, 1.0654)	.1708		0.8922 (0.6847, 1.1626)	.3984		0.0005 (0.0000, Inf)	.9985
Other races	0.8245 (0.7481, 0.9087)	.0001		0.9292 (0.8311, 1.0390)	.1977		0.9273 (0.8156, 1.0542)	.2489
BMI^d			0.9420			0.9311			0.8375
Normal BMI	0.9050 (0.8505, 0.9630)	.0016		0.9472 (0.8842, 1.0147)	.1227		0.9151 (0.8460, 0.9899)	.0269
Overweight	0.9153 (0.8496, 0.9860)	.0198		0.9391 (0.8639, 1.0209)	.1403		0.9342 (0.8521, 1.0242)	.1469
Obesity	0.8978 (0.8266, 0.9751)	.0105		0.9036 (0.8255, 0.9891)	.0280		0.8872 (0.8041, 0.9789)	.0171

Model 1: no covariates were adjusted; Model 2: age, sex/menopausal status, race/ethnicity, and BMI were adjusted; Model 3: all covariates were adjusted.

BMI: body mass index; CI: confidence interval; OR: odds ratio; UHR: uric acid to high-density lipoprotein cholesterol ratio.

^aAge was not adjusted.

^bSex/menopausal status was not adjusted.

^cRace/ethnicity was not adjusted.

^dBMI was not adjusted.

Sensitivity analysis

When UHR was converted from a continuous variable to a categorical variable (Q1–Q4), linear regression analysis showed that individuals with the highest UHR (Q4) exhibited higher FN-BMD compared to those with the lowest UHR (Q1). Additionally, logistic regression analysis indicated that individuals with a higher UHR (Q3 and Q4) had a lower risk of osteoporosis compared to those with the lowest UHR (Q1). Detailed results are presented in Table 4.

Table 4.

Association between UHR (Q1 to Q4) and FN-BMD (and the risk of osteoporosis).

Outcome	Subgroup	Model 1		Model 2		Model 3
Outcome	Subgroup	β/OR (95% CI)	p-value	β/OR (95% CI)	p-value	β/OR (95% CI)	p-value
FN-BMD	UHR (Q1)	Reference (0)	—	Reference (0)	—	Reference (0)	—
	UHR (Q2)	0.0464 (0.0318, 0.0611)	<.0001	0.0057 (−0.0074, 0.0188)	.3952	0.0079 (−0.0051, 0.0209)	.2356
	UHR (Q3)	0.0690 (0.0543, 0.0836)	<.0001	0.0112 (−0.0024, 0.0249)	.1070	0.0126 (−0.0012, 0.0263)	.0728
	UHR (Q4)	0.0967 (0.0821, 0.1113)	<.0001	0.0164 (0.0017, 0.0311)	.0285	0.0180 (0.0031, 0.0328)	.0181
Non-osteoporosis vs. Osteoporosis	UHR (Q1)	Reference (1)	—	Reference (1)	—	Reference (1)	—
	UHR (Q2)	0.5418 (0.3727, 0.7877)	.0013	0.8622 (0.5712, 1.3015)	.4805	0.7868 (0.5158, 1.2002)	.2657
	UHR (Q3)	0.4097 (0.2730, 0.6149)	.0001	0.7240 (0.4571, 1.1467)	.1687	0.6094 (0.3782, 0.9821)	.0419
	UHR (Q4)	0.1992 (0.1183, 0.3354)	<.0001	0.4678 (0.2586, 0.8461)	.0120	0.3948 (0.2137, 0.7296)	.0030

Model 1: no covariates were adjusted; Model 2: age, sex/menopausal status, race/ethnicity, and BMI were adjusted; Model 3: all covariates were adjusted.

BMD: bone mineral density; CI: confidence interval; FN: femoral neck; OR: odds ratio; UHR: uric acid to high-density lipoprotein cholesterol ratio.

Discussion

The increasing incidence of osteoporosis among middle-aged and elderly individuals, which significantly diminishes the quality of life for older adults, has established osteoporosis as a global public health concern.^1,12 In this cross-sectional study, UHR was positively associated with FN-BMD and negatively associated with osteoporosis risk in individuals aged ≥50 years. Subgroup analyses further revealed that the positive association between UHR and FN-BMD was observed in individuals aged ≥65 years, but not in those aged 50–64 years, with interaction analysis confirming significant age-related differences after adjusting for all covariates.

This study identified a positive association between UHR and BMD, with a higher UHR associated with a reduced risk of osteoporosis. Previous research has reported a positive association between UA levels and BMD.^31–34 For instance, Jin et al. reported a positive association between UA and BMD in males aged ≥50 years,³³ while Xu et al. reported that serum UA levels were positively associated with BMD among patients with osteoporosis.³⁴ Yao et al. demonstrated a positive correlation between UA and lumbar spine BMD in elderly individuals.³⁵ However, the relationship between HDL-C and BMD remains contentious, as several studies have indicated a negative correlation between HDL-C and BMD.^36,37 Tang et al. observed a negative association between HDL-C and BMD in individuals aged ≥20 years.³⁶ Wang et al. identified a similar negative correlation in male adolescents aged 12 to 19 years, particularly among non-black and non-Mexican populations.³⁷ In contrast, Xie et al. reported a positive correlation between HDL-C and lumbar spine BMD in individuals aged 20 to 59 years.³⁸ The aforementioned findings might contribute to the observed positive association between UHR and BMD. However, further research with larger sample sizes is necessary to elucidate the relationship between UHR and BMD.

The current study identified a positive correlation between UHR and FN-BMD in individuals aged ≥65 years, but not in those aged 50 to 64 years. This discrepancy might be attributed to several factors. The prevalence of osteoporosis increases significantly with age,^1,7,12 and age itself is a significant independent factor influencing BMD.^1,6,12 Additionally, the relatively small sample size of individuals with osteoporosis in the 50–64 age group (N = 56) in this study might have limited the ability to detect a similar association. Therefore, further research is needed to better understand these age-related differences.

The main findings of this study might have implications for future research. The novel inflammation and metabolic indicator, UHR—comprising UA and HDL-C—has been associated with various clinical conditions such as hypertension, diabetes, metabolic syndrome, and non-alcoholic fatty liver disease.^18,39–41 To the best of our knowledge, this is the first study to investigate the association between UHR and BMD, as well as the risk of osteoporosis. Importantly, it was found that higher UHR values were associated with a reduced osteoporosis risk, suggesting that UHR could serve as a novel indicator for identifying and predicting osteoporosis risk. Furthermore, the study revealed that the correlation between UHR and FN-BMD was significant only in individuals aged ≥65 years, not in those aged 50 to 64 years. The interaction analysis further highlighted significant age-related differences after adjusting for covariates. Although the reasons for these age disparities remain unclear, it is imperative to consider age differences when using UHR as a marker for osteoporosis risk prediction.

This study has several limitations that should be acknowledged. First, due to its cross-sectional design, the study does not allow for causal interpretations between UHR and osteoporosis. Second, some covariates were collected through self-reported questionnaires, which might introduce recall bias. Third, the sample size of participants with osteoporosis was relatively small. Further studies with large sample sizes are needed to better understand the relationship between UHR and osteoporosis risk. Lastly, since all participants were from the US, the findings might not apply to populations in other countries.

Conclusion

Clinicians should be vigilant about the potential risk of osteoporosis in individuals with low UHR, as UHR could serve as a risk indicator for this condition.

Supplemental Material

Supplemental Material - Uric acid-to-high-density lipoprotein cholesterol ratio and osteoporosis: evidence from the national health and nutrition examination survey

Supplemental Material for Uric acid-to-high-density lipoprotein cholesterol ratio and osteoporosis: evidence from the national health and nutrition examination survey by Zeyu Liu, Yuchen Tang, Ying Sun, Miao Lei, Minghuang Cheng, Xiaohan Pan, Zhenming Hu and Jie Hao in Journal of Orthopaedic Surgery

Footnotes

Acknowledgements

We thank Bullet Edits Limited for the linguistic editing and proofreading of the manuscript. The authors extend their gratitude to the participants for their time and effort during the data collection phase of the NHANES project.

Author contributions

ZL and YT have contributed equally to this work. ZL: Conceptualisation, Formal analysis, Data Curation, Writing-Original Draft, and Writing-Review & Editing; YT: Conceptualisation, Methodology, Validation, Writing-Original Draft, and Writing-Review & Editing; YS: Software, Data Curation, Visualisation, and Writing-Review & Editing; ML: Validation and Writing-Review & Editing; MC: Software and Writing-Review & Editing; XP: Investigation and Writing-Review & Editing; ZH: Conceptualisation, Writing-Review & Editing and Supervision; JH: Conceptualisation, Methodology, Writing-Review & Editing, and Supervision.

Declaration of conflicting interests

The author(s) declare that there are no potential conflicts of interest related to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical statement

ORCID iD

Zeyu Liu

Data availability statement

The datasets obtained and analysed in the present study are publicly available on the NHANES database ().

Supplemental Material

Supplemental material for this article is available online.

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